Figure 1

Antigen persists in discrete cell populations within the lymph node

  1. Experimental design
  2. UMAP projections show LEC and DC subsets
  3. Antigen signal is shown for LEC subsets for each time point
  4. Antigen signal is shown for DC subsets for each time point




Figure 2

Identification of an antigen archiving gene signature

  1. Ag-scores are shown for dat 14 Ag-high and Ag-low cells
  2. The top 3 gene ontology terms are shown for Ag-high gene modules
  3. The expression of each Ag-high gene module is shown for naive LECs (day 0) along with each immunization time point.




Figure 3

Predicting antigen archiving ability

  1. The fraction of cells predicted to be Ag-competent is shown for LECs
  2. F1 scores are shown for random forest models trained using day 14 LECs
  3. Ag-high module scores are shown for predicted Ag-competent LECs
  4. Select example genes from the cLEC Ag-high gene module are shown, triangles indicate the gene is upregulated when compared to Ag-low




Figure 4

Antigen archiving is enhanced by sequential vaccinations

  1. Experimental design
  2. Ag-score is shown for single and dual vaccinations for the 21 day timepoint for each LEC subset. Other timepoints are shown in grey. P values were calculated using a one-sided Wilcoxon rank sum test with Benjamini-Hochberg correction.
  3. Successive vaccinations enhances retention of previously archived antigen. Ag-score is shown for the 42 day timepoint as described in C.
  4. Ag-high module scores described in Figure 2 are shown for LECs that archived antigens from both vaccinations (double-high), from only one vaccination (single-high), or have low levels of both antigens (Ag-low). Module scores are shown for the corresponding LEC subset. P values were calculated using a one-sided Wilcoxon rank sum test with Benjamini-Hochberg correction.




Figure 5

Antigen exchange with DCs correlates with levels of antigen archiving

  1. Annotated regions, segment types, and antigen signal is shown for a representative lymph node analyzed using the GeoMx DSP platform
  2. Relative antigen signal is shown for each region segmented based on Lyve1 (LECs) and CD11C (DCs)
  3. Antigen signal is shown for regions that included both Lyve1+ and CD11C+ segments




Figure 6

Antigen archiving is impaired during CHIKV infection

  1. The fraction of predicted Ag-competent cLECs is shown for mock and CHIKV-infected mice
  2. cLEC Ag-high module scores are shown for mock and CHIKV-infected mice
  3. The percentage of ova+ LECs for mice infected with WT CHIKV or an attenuated strain (CHIKV 181/25)




Session info

## R version 4.3.1 (2023-06-16)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 22.04.4 LTS
## 
## Matrix products: default
## BLAS:   /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3 
## LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.20.so;  LAPACK version 3.10.0
## 
## locale:
##  [1] LC_CTYPE=en_US.UTF-8          LC_NUMERIC=C                 
##  [3] LC_TIME=en_US.UTF-8           LC_COLLATE=en_US.UTF-8       
##  [5] LC_MONETARY=en_US.UTF-8       LC_MESSAGES=en_US.UTF-8      
##  [7] LC_PAPER=en_US.UTF-8          LC_NAME=en_US.UTF-8          
##  [9] LC_ADDRESS=en_US.UTF-8        LC_TELEPHONE=en_US.UTF-8     
## [11] LC_MEASUREMENT=en_US.UTF-8    LC_IDENTIFICATION=en_US.UTF-8
## 
## time zone: America/Denver
## tzcode source: system (glibc)
## 
## attached base packages:
##  [1] grid      tools     stats4    stats     graphics  grDevices utils    
##  [8] datasets  methods   base     
## 
## other attached packages:
##  [1] SpatialOmicsOverlay_1.0.0 umap_0.2.10.0            
##  [3] GeoMxWorkflows_1.6.0      GeomxTools_3.4.0         
##  [5] NanoStringNCTools_1.8.0   cli_3.6.1                
##  [7] devtools_2.4.5            usethis_2.2.2            
##  [9] here_1.0.1                broom_1.0.5              
## [11] knitr_1.44                lubridate_1.9.3          
## [13] forcats_1.0.0             stringr_1.5.0            
## [15] dplyr_1.1.3               purrr_1.0.2              
## [17] readr_2.1.4               tidyr_1.3.0              
## [19] tibble_3.2.1              tidyverse_2.0.0          
## [21] png_0.1-8                 ComplexHeatmap_2.16.0    
## [23] xlsx_0.6.5                openxlsx_4.2.5.2         
## [25] qs_0.25.5                 ggtree_3.8.2             
## [27] MetBrewer_0.2.0           ggtrace_0.2.0.9000       
## [29] ggtext_0.1.2              patchwork_1.1.3          
## [31] colorblindr_0.1.0         colorspace_2.1-0         
## [33] RColorBrewer_1.1-3        ggrepel_0.9.3            
## [35] cowplot_1.1.1             ggbeeswarm_0.7.2         
## [37] ggforce_0.4.1             scales_1.2.1             
## [39] caret_6.0-94              lattice_0.21-8           
## [41] ggplot2_3.4.4             furrr_0.3.1              
## [43] future_1.33.0             ranger_0.15.1            
## [45] rsample_1.2.0             gtools_3.9.4             
## [47] boot_1.3-28.1             mixtools_2.0.0           
## [49] GOSemSim_2.26.1           org.Mm.eg.db_3.17.0      
## [51] AnnotationDbi_1.62.2      IRanges_2.34.1           
## [53] S4Vectors_0.38.2          Biobase_2.60.0           
## [55] BiocGenerics_0.46.0       msigdbr_7.5.1            
## [57] enrichplot_1.20.3         clusterProfiler_4.8.3    
## [59] biomaRt_2.56.1            gprofiler2_0.2.2         
## [61] M3Drop_1.26.0             numDeriv_2016.8-1.1      
## [63] djvdj_0.1.0               harmony_1.1.0            
## [65] presto_1.0.0              data.table_1.14.8        
## [67] Rcpp_1.0.11               clustifyrdata_1.1.0      
## [69] clustifyr_1.12.0          SeuratObject_4.1.4       
## [71] Seurat_4.4.0             
## 
## loaded via a namespace (and not attached):
##   [1] igraph_1.5.1                ica_1.0-3                  
##   [3] plotly_4.10.2               Formula_1.2-5              
##   [5] zlibbioc_1.46.0             tidyselect_1.2.0           
##   [7] bit_4.0.5                   doParallel_1.0.17          
##   [9] clue_0.3-65                 rjson_0.2.21               
##  [11] blob_1.2.4                  urlchecker_1.0.1           
##  [13] S4Arrays_1.0.6              parallel_4.3.1             
##  [15] plotrix_3.8-4               ggplotify_0.1.2            
##  [17] outliers_0.15               askpass_1.2.0              
##  [19] openssl_2.1.1               goftest_1.2-3              
##  [21] kernlab_0.9-32              densEstBayes_1.0-2.2       
##  [23] uwot_0.1.16                 shadowtext_0.1.2           
##  [25] curl_5.1.0                  mime_0.12                  
##  [27] evaluate_0.22               tidytree_0.4.5             
##  [29] tiff_0.1-12                 leiden_0.4.3               
##  [31] stringi_1.7.12              pROC_1.18.5                
##  [33] backports_1.4.1             lmerTest_3.1-3             
##  [35] XML_3.99-0.14               httpuv_1.6.11              
##  [37] magrittr_2.0.3              rappdirs_0.3.3             
##  [39] splines_4.3.1               prodlim_2023.08.28         
##  [41] RApiSerialize_0.1.2         jpeg_0.1-10                
##  [43] ggraph_2.1.0                sctransform_0.4.0          
##  [45] sessioninfo_1.2.2           DBI_1.1.3                  
##  [47] jquerylib_0.1.4             withr_2.5.1                
##  [49] systemfonts_1.0.4           class_7.3-22               
##  [51] rprojroot_2.0.3             lmtest_0.9-40              
##  [53] bdsmatrix_1.3-6             tidygraph_1.2.3            
##  [55] BiocManager_1.30.22         htmlwidgets_1.6.2          
##  [57] fs_1.6.3                    SingleCellExperiment_1.22.0
##  [59] segmented_1.6-4             labeling_0.4.3             
##  [61] cellranger_1.1.0            MatrixGenerics_1.12.3      
##  [63] reticulate_1.32.0           zoo_1.8-12                 
##  [65] GGally_2.2.0                XVector_0.40.0             
##  [67] timechange_0.2.0            foreach_1.5.2              
##  [69] fansi_1.0.5                 caTools_1.18.2             
##  [71] timeDate_4022.108           ggiraph_0.8.7              
##  [73] RSpectra_0.16-1             irlba_2.3.5.1              
##  [75] gridGraphics_0.5-1          ellipsis_0.3.2             
##  [77] lazyeval_0.2.2              yaml_2.3.7                 
##  [79] survival_3.5-5              scattermore_1.2            
##  [81] crayon_1.5.2                RcppAnnoy_0.0.21           
##  [83] progressr_0.14.0            tweenr_2.0.2               
##  [85] later_1.3.1                 ggridges_0.5.4             
##  [87] codetools_0.2-19            base64enc_0.1-3            
##  [89] GlobalOptions_0.1.2         profvis_0.3.8              
##  [91] KEGGREST_1.40.1             bbmle_1.0.25               
##  [93] Rtsne_0.16                  shape_1.4.6                
##  [95] filelock_1.0.2              foreign_0.8-84             
##  [97] pkgconfig_2.0.3             xml2_1.3.5                 
##  [99] EnvStats_2.8.1              GenomicRanges_1.52.1       
## [101] aplot_0.2.2                 spatstat.sparse_3.0-2      
## [103] ape_5.7-1                   viridisLite_0.4.2          
## [105] xtable_1.8-4                plyr_1.8.9                 
## [107] httr_1.4.7                  globals_0.16.2             
## [109] hardhat_1.3.0               pkgbuild_1.4.2             
## [111] beeswarm_0.4.0              htmlTable_2.4.2            
## [113] checkmate_2.3.0             nlme_3.1-162               
## [115] loo_2.6.0                   HDO.db_0.99.1              
## [117] dbplyr_2.3.4                lme4_1.1-35.1              
## [119] digest_0.6.33               Matrix_1.6-1.1             
## [121] farver_2.1.1                tzdb_0.4.0                 
## [123] reshape2_1.4.4              ModelMetrics_1.2.2.2       
## [125] yulab.utils_0.1.0           viridis_0.6.4              
## [127] rpart_4.1.19                glue_1.6.2                 
## [129] cachem_1.0.8                BiocFileCache_2.8.0        
## [131] polyclip_1.10-6             Hmisc_5.1-1                
## [133] generics_0.1.3              Biostrings_2.68.1          
## [135] mvtnorm_1.2-3               parallelly_1.36.0          
## [137] pkgload_1.3.3               statmod_1.5.0              
## [139] minqa_1.2.6                 pbapply_1.7-2              
## [141] SummarizedExperiment_1.30.2 vroom_1.6.4                
## [143] gson_0.1.0                  utf8_1.2.3                 
## [145] gower_1.0.1                 graphlayouts_1.0.2         
## [147] StanHeaders_2.26.28         readxl_1.4.3               
## [149] gridExtra_2.3               shiny_1.7.5                
## [151] lava_1.7.3                  GenomeInfoDbData_1.2.10    
## [153] RCurl_1.98-1.12             memoise_2.0.1              
## [155] rmarkdown_2.25              pheatmap_1.0.12            
## [157] downloader_0.4              RANN_2.6.1                 
## [159] stringfish_0.15.8           spatstat.data_3.0-1        
## [161] rstudioapi_0.15.0           cluster_2.1.4              
## [163] QuickJSR_1.0.7              rstantools_2.3.1.1         
## [165] spatstat.utils_3.0-3        hms_1.1.3                  
## [167] fitdistrplus_1.1-11         munsell_0.5.0              
## [169] rlang_1.1.1                 GenomeInfoDb_1.36.4        
## [171] ipred_0.9-14                circlize_0.4.15            
## [173] mgcv_1.8-42                 xfun_0.40                  
## [175] remotes_2.4.2.1             recipes_1.0.8              
## [177] iterators_1.0.14            matrixStats_1.0.0          
## [179] reldist_1.7-2               abind_1.4-5                
## [181] rstan_2.32.3                treeio_1.24.3              
## [183] rJava_1.0-6                 fftwtools_0.9-11           
## [185] bitops_1.0-7                ps_1.7.5                   
## [187] promises_1.2.1              inline_0.3.19              
## [189] scatterpie_0.2.1            RSQLite_2.3.1              
## [191] qvalue_2.32.0               fgsea_1.26.0               
## [193] DelayedArray_0.26.7         GO.db_3.17.0               
## [195] compiler_4.3.1              RBioFormats_1.0.0          
## [197] prettyunits_1.2.0           listenv_0.9.0              
## [199] tensor_1.5                  MASS_7.3-60                
## [201] progress_1.2.2              uuid_1.1-1                 
## [203] BiocParallel_1.34.2         gridtext_0.1.5             
## [205] EBImage_4.42.0              babelgene_22.9             
## [207] spatstat.random_3.1-6       R6_2.5.1                   
## [209] fastmap_1.1.1               fastmatch_1.1-4            
## [211] vipor_0.4.5                 ROCR_1.0-11                
## [213] ggstats_0.5.1               nnet_7.3-19                
## [215] gtable_0.3.4                KernSmooth_2.23-21         
## [217] miniUI_0.1.1.1              deldir_1.0-9               
## [219] ggthemes_5.0.0              htmltools_0.5.6.1          
## [221] RcppParallel_5.1.7          bit64_4.0.5                
## [223] spatstat.explore_3.2-3      lifecycle_1.0.3            
## [225] zip_2.3.0                   processx_3.8.2             
## [227] nloptr_2.0.3                callr_3.7.3                
## [229] xlsxjars_0.6.1              sass_0.4.7                 
## [231] vctrs_0.6.3                 spatstat.geom_3.2-5        
## [233] DOSE_3.26.2                 ggfun_0.1.3                
## [235] sp_2.1-0                    future.apply_1.11.0        
## [237] entropy_1.3.1               bslib_0.5.1                
## [239] pillar_1.9.0                magick_2.8.2               
## [241] gplots_3.1.3                locfit_1.5-9.8             
## [243] BiocStyle_2.28.1            jsonlite_1.8.7             
## [245] GetoptLong_1.0.5